Large-scale computing currently has at least two significant limitations and/or drawbacks. The first obstacle is that computers require electrical power in order to operate and perform their calculations. Some of the power energizes the CPUs while remaining power energizes the random-access memory, shared and/or more persistent memory (e.g. hard disks), switches, routers, and other equipment supporting network connections between computers. As society's reliance on computers and computing increases, the portion of the world's energy budget that is consumed by computers and computing also increases. By some estimates, computers and computing currently account for approximately 4% of the world's total electricity budget and is growing at an exponential pace, especially with respect to computationally intensive tasks such as simulations, artificial intelligence, and the mining of cryptocurrencies such as Bitcoin.
The second obstacle to large scale computing is that computers generate heat. Most of the electrical power used to energize computers is converted to, and/or lost as, heat from the circuits and components that execute the respective computational tasks. The heat generated by computers can raise the temperatures of computers to levels that can cause those computers to fail, especially when the computers are located in close proximity to one another. Because of this, computers and the environments in which they operate must be cooled. This cooling, e.g. through air conditioners and fans, consumes significant electrical power over and above the electrical power used to energize the computers. Favorable historical trends in the miniaturization of computer components (e.g. “Moore's Law”) are currently slowing, suggesting that future increases in computational power may require greater investments in cooling than was common in the past.